Computer-implemented method, data-processing device, non-invasive brain-computer interface system and non-transitory computer readable medium

Abstract

A computer-implemented method for obtaining continuous signals from biopotential signals, including: separating, by a computer, confounding components from the biopotential signals by using a statistical correlation analysis algorithm to obtain denoised neural signals; and decoding, by the computer, the continuous signals from the denoised neural signals.

What is claimed is: 
     
         1 . A computer-implemented method for obtaining continuous signals from biopotential signals, comprising:
 separating, by a computer, confounding components from the biopotential signals by using a statistical correlation analysis algorithm to obtain denoised neural signals; and   decoding, by the computer, the continuous signals from the denoised neural signals.   
     
     
         2 . The computer-implemented method according to  claim 1 , wherein the continuous signals are continuous motor action commands. 
     
     
         3 . The computer-implemented method according to  claim 1 , wherein the statistical correlation analysis algorithm is a Canonical Correlation Analysis algorithm. 
     
     
         4 . The computer-implemented method according to  claim 1 , wherein the statistical correlation analysis algorithm is performed using a model based on an existing dataset of biopotential signals and correlated motion data, vision, acoustic or other biopotential data. 
     
     
         5 . The computer-implemented method according to  claim 4 , wherein the correlated motion data include EMG data, motion sensor data or visual motion capture data. 
     
     
         6 . The computer-implemented method according to  claim 1 , wherein the decoding the continuous signals from the denoised neural signals is performed using a Multiple Linear Regression model. 
     
     
         7 . The computer-implemented method according to  claim 6 , wherein the Multiple Linear Regression model correlates the continuous signals to the denoised neural signals within an anticipating time window. 
     
     
         8 . The computer-implemented method according to  claim 1 , further comprising filtering the biopotential signals before the separating the confounding components. 
     
     
         9 . The computer-implemented method according to  claim 1 , further comprising operating a machine using the continuous signals as command signals. 
     
     
         10 . The computer-implemented method according to  claim 9 , wherein the machine is a vehicle. 
     
     
         11 . The computer-implemented method according to  claim 9 , wherein the machine is a robotic manipulator. 
     
     
         12 . The computer-implemented method according to  claim 9 , wherein the machine is a prosthetic device. 
     
     
         13 . The computer-implemented method according to  claim 1 , further comprising verifying whether the continuous signals correspond to continuous commands within a set of acceptable continuous commands. 
     
     
         14 . The computer-implemented method according to  claim 1 , further comprising comparing, by the computer, the continuous signals to a response of a machine operated by a human user generating the biopotential signals. 
     
     
         15 . A data processing device comprising a processor configured to perform the computer-implemented method according to  claim 1 . 
     
     
         16 . A non-invasive brain-machine interface system comprising a data processing device according to  claim 15  and an EEG electrode array or an EMG electrode array connected to the data processing device. 
     
     
         17 . A non-transitory computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the computer-implemented method according to  claim 1 .